Background:

Scleroderma Renal Crisis (SRC) is a life-threatening complication of systemic sclerosis (SSc). The Major Histocompatibility Region (MHC) showed the strongest association with SSc in a recently published large genome-wide association study, raising the possibility that this gene locus might be also important for biomarker development. The predictive significance of MHC genetic markers for SRC has not been previously investigated. The goal of the current study was to examine the predictive role of MHC genetic markers for the SRC beyond the known clinical correlates in a large population of patients with SSc.

Methods:

SSc patients from the Scleroderma Family Registry and DNA Repository, Genetics versus Environment in Scleroderma Outcomes Study (GENISOS) and divisional registry at the University of Texas Health Science Center at Houston were included in the study. Patients, enrolled in more than one of the above mentioned sources, were identified and duplicate entries were omitted. ANA, anticentromere (ACA), anti-topoisomerase (ATA), and anti-RNA polymerase III (ARA) antibodies were detected utilizing commercially available kits. Furthermore, HLA Class II genotyping (DRB1, DQA1, DPB1) was performed on extracted and purified genomic DNA. Multivariate models were constructed following a purposeful variable selection method. First, we evaluated the demographic and clinical variables without genetic risk factors for their multivariable associations with SRC. Subsequently, we conducted a separate purposeful model building analysis after addition of the MHC genetic data. Ethnicities were included in all univariate and multivariable genetic analysis models.

Results:

Overall, 1519 patients with SSc were included in this study, from which 90 patients (5.9%) had developed SRC. Of the 90 patients with SRC, diffuse cutaneous subtypes were found in 76%, ATA in 9%, ACA in 2%, and ARA in 50%. ARA and diffuse disease type were independent risk factors for presence of SRC, whereas ACA and ATA were protective in the multivariate model of clinical variables. In the final multivariable analysis after inclusion of HLA allotypes, we identified HLA-DRB1*0407 (OR=3.21, 95% CI 1.278.08; P=0.013) and *1304 (OR=4.51, 95% CI 1.3015.68; P=0.018) as independent risk factors for SRC. Only 3 clinical characteristics, ARA, diffuse disease type and ACA remained statistically significant in the final model.

Conclusion:

This study suggests that HLA DRB1*0407 and *1304 can be used as biomarkers for identification of SSc patients at risk for developing SRC beyond the information provided by known clinical predictors.